Adversarial machine learning for network intrusion detection systems: A comprehensive survey
Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …
network attacks that compromise the security of the data, systems, and networks. In recent …
[HTML][HTML] Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review
M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …
Anomaly-based intrusion detection system for IoT networks through deep learning model
Abstract The Internet of Things (IoT) idea has been developed to enhance people's lives by
delivering a diverse range of smart interconnected devices and applications in several …
delivering a diverse range of smart interconnected devices and applications in several …
[HTML][HTML] A machine learning-based intrusion detection for detecting internet of things network attacks
Abstract The Internet of Things (IoT) refers to the collection of all those devices that could
connect to the Internet to collect and share data. The introduction of varied devices …
connect to the Internet to collect and share data. The introduction of varied devices …
A review on digital twin technology in smart grid, transportation system and smart city: Challenges and future
With recent advances in information and communication technology (ICT), the bleeding
edge concept of digital twin (DT) has enticed the attention of many researchers to …
edge concept of digital twin (DT) has enticed the attention of many researchers to …
[HTML][HTML] A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and …
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
[HTML][HTML] Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects
Internet of Things (IoT) is a developing technology that provides the simplicity and benefits of
exchanging data with other devices using the cloud or wireless networks. However, the …
exchanging data with other devices using the cloud or wireless networks. However, the …
Applications of artificial intelligence and machine learning in smart cities
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …
maintain a green environment, improve the economic and living standards of their citizens …
Deep learning methods in network intrusion detection: A survey and an objective comparison
S Gamage, J Samarabandu - Journal of Network and Computer …, 2020 - Elsevier
The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …
area of research in cybersecurity. Although several excellent surveys cover the growing …
Internet of things intrusion detection: Centralized, on-device, or federated learning?
With the ever increasing number of cyber-attacks, internet of Things (ioT) devices are being
exposed to serious malware, attacks, and malicious activities alongside their development …
exposed to serious malware, attacks, and malicious activities alongside their development …